scholarly journals Analyzing the Impact of Trucks on Traffic Flow Based on an Improved Cellular Automaton Model

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Dewen Kong ◽  
Xiucheng Guo ◽  
Bo Yang ◽  
Dingxin Wu
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Volume ◽  
Cellular Automaton Model ◽  
Passenger Cars ◽  
Passenger Car ◽  
Car Following ◽  
Proposed Model ◽  
The Impact

This paper aims to analyze the impact of trucks on traffic flow and propose an improved cellular automaton model, which considers both the performance difference between passenger cars and trucks and the behaviour change of passenger cars under the impact of trucks. A questionnaire survey has been conducted to find out whether the impact of trucks exists and how the behaviour of passenger car drivers changes under the impact of trucks. The survey results confirm that the impact of trucks exists and indicate that passenger car drivers will enlarge the space gap, decelerate, and change lanes in advance when they are affected. Simulation results show that traffic volume is still affected by percentages of trucks in the congestion phase in the proposed model compared with traditional heterogeneous cellular automaton models. Traffic volume and speed decrease with the impact of trucks in the congestion phase. The impact of trucks can increase traffic congestion as it increases. However, it has different influences on the speed variance of passenger cars in different occupancies. In the proposed model, the relative relationship of the space gap between car-following-truck and car-following-car is changeable at a certain value of occupancy, which is related to the impact of trucks.

scholarly journals An Improved Single-Lane Cellular Automaton Model considering Driver’s Radical Feature

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xu Qu ◽  
Mofeng Yang ◽  
Fan Yang ◽  
Bin Ran ◽  
Linchao Li
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Early Stage ◽  
Cellular Automaton Model ◽  
Fundamental Diagram ◽  
Flow Models ◽  
Car Following ◽  
Speed Difference ◽  
Density State ◽  
Traffic Flow Models

Traffic flow models are of vital significance to study the traffic system and reproduce typical traffic phenomena. In the process of establishing traffic flow models, human factors need to be considered particularly to enhance the performance of the models. Accordingly, a series of car-following models and cellular automaton models were proposed based on comprehensive consideration of various driving behaviors. Based on the comfortable driving (CD) model, this paper innovatively proposed an improved cellular automaton model incorporating impaired driver’s radical feature (RF). The impaired driver’s radical feature was added to the model with respect to three aspects, that is, desired speed, car-following behavior, and braking behavior. Empirical data obtained from a highway segment was used to initialize impaired driver’s radical feature distribution and calibrate the proposed model. Then, numerical simulations validated that the proposed improved model can well reproduce the traffic phenomena, as shown by the fundamental diagram and space-time diagram. Also, in low-density state, it can be found that the RF model is superior to the CD model in simulating the speed difference characteristics, where the average speed difference of adjacent vehicles for RF model is more consistent with reality. The result also discussed the potential impact of impaired drivers on rear-end collisions. It should be noted that this study is an early stage work to evaluate the existence of impaired driving behavior.

Stability analysis of car-following model on straight and curved roads considering the preceding vehicle’s velocity feedback control

2018 ◽  
Vol 32 (21) ◽  
pp. 1850238 ◽  
Author(s):  
Peng Tan ◽  
Di-Hua Sun ◽  
Dong Chen ◽  
Min Zhao ◽  
Tao Chen
Keyword(s):  
Feedback Control ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Velocity Feedback ◽  
Car Following ◽  
Car Following Model ◽  
Negative Feedback Control ◽  
The Stability ◽  
The Impact ◽  
Good Agreement

In order to reveal the impact of preceding vehicle’s velocity on traffic flow, an extended car-following model considering preceding vehicle’s velocity feedback control is proposed in this paper. The linear stability criterion of the new model is derived through control theory method and it shows that the feedback control signal impacts the stability of traffic flow. Numerical simulation results is in good agreement with the theoretical analysis, which prove that a smaller negative feedback control of the preceding vehicle’s velocity can enhance the stability of traffic flow, while a smaller positive feedback control of the preceding vehicle’s velocity can exacerbate traffic congestion. Moreover, the reaction coefficients of straight and curved road conditions also play an important role in the stability of traffic flow.

TRAFFIC FLOW INFLUENCED BY TRAFFIC LIGHT AND TURNING PROBABILITY FOR A CROSSROAD

2004 ◽  
Vol 18 (17n19) ◽  
pp. 2658-2662 ◽  
Author(s):  
HUILI TAN ◽  
CHAOYING ZHANG ◽  
LINGJIANG KONG ◽  
MUREN LIU
Keyword(s):  
Boundary Condition ◽  
Cellular Automaton ◽  
Traffic Flow ◽  
Cellular Automaton Model ◽  
Open Boundary ◽  
Open Boundary Condition ◽  
Traffic Light ◽  
Cycle Times ◽  
The Road ◽  
The Impact

A cellular automaton model with open boundary condition for a crossroad system controlled by a traffic light is presented. The traffic flow and speed of the first part of the road are quite different from those of the second part behind the crossing. The impact of turning probabilities and the cycle times of traffic light on the flow are investigated.

scholarly journals An Improved Car-Following Model considering Desired Safety Distance and Heterogeneity of Driver’s Sensitivity

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Lei Zhang ◽  
Shengrui Zhang ◽  
Bei Zhou ◽  
Shuaiyang Jiao ◽  
Yan Huang
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Dynamic Performance ◽  
Velocity Function ◽  
Optimal Velocity ◽  
Car Following ◽  
Safety Distance ◽  
Proposed Model ◽  
Car Following Model ◽  
Optimal Velocity Function

We investigate the dynamic performance of traffic flow using a modified optimal velocity car-following model. In the car-following scenarios, the following vehicle must continuously adjust the following distance to the preceding vehicle in real time. A new optimal velocity function incorporating the desired safety distance instead of a preset constant is presented first to describe the abovementioned car-following behavior dynamically. The boundary conditions of the new optimal velocity function are theoretically analyzed. Subsequently, we propose an improved car-following model by combining the heterogeneity of driver’s sensitivity based on the new optimal velocity function and previous car-following model. The stability criterion of the improved model is obtained through the linear analysis method. Finally, numerical simulation is performed to explore the effect of the desired safety distance and the heterogeneity of driver’s sensitivity on the traffic flow. Results show that the proposed model has considerable effects on improving traffic stability and suppressing traffic congestion. Furthermore, the proposed model is compatible with the heterogeneity of driver’s sensitivity and can enhance the average velocity of traffic flow compared with the conventional model. In conclusion, the dynamic performance of traffic flow can be improved by considering the desired safety distance and the heterogeneity of driver’s sensitivity in the car-following model.

The impact of aggressive driving behaviors on multi-lane highway traffic flow

2018 ◽  
Vol 29 (07) ◽  
pp. 1850056 ◽  
Author(s):  
H. B. Zhu ◽  
G. Y. Chen ◽  
H. Lin ◽  
Y. J. Zhou
Keyword(s):  
Traffic Flow ◽  
High Speed ◽  
Aggressive Driving ◽  
Highway Traffic ◽  
Lane Changing ◽  
Car Following ◽  
Driving Behaviors ◽  
Evolution Pattern ◽  
Proposed Model ◽  
The Impact

A modified cellular automata traffic model is proposed to simulate four-lane traffic flow, in which drivers are classified into aggressive drivers and cautious drivers and the anticipative velocity of the adjacent vehicles is considered. Analysis from the vehicles’ evolution pattern indicates that vehicles driven by the aggressive drivers are more powerful in behaviors of lane-changing and car-following. The model is refined by using the small cell of one meter long in order to simulate the traffic flow meticulously and realistically. The results indicate that the lane-changing maneuver exhibits different property as the density varies, and it does have a significant impact on the characteristics of the surrounding traffic flow due to their interfering effects on the following vehicles. Furthermore, the phenomenon of high-speed car-following is exhibited, and the results coincide with the empirical data very well. It is shown that the proposed model is reasonable and can partially reflect the real traffic.

scholarly journals An Extended Car-Following Model Considering Generalized Preceding Vehicles in V2X Environment

2020 ◽  
Vol 12 (12) ◽  
pp. 216
Author(s):  
Junyan Han ◽  
Jinglei Zhang ◽  
Xiaoyuan Wang ◽  
Yaqi Liu ◽  
Quanzheng Wang ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Neutral Stability ◽  
State Information ◽  
Car Following ◽  
Motion State ◽  
Car Following Model ◽  
The Impact ◽  
Good Agreement

Vehicle-to-everything (V2X) technology will significantly enhance the information perception ability of drivers and assist them in optimizing car-following behavior. Utilizing V2X technology, drivers could obtain motion state information of the front vehicle, non-neighboring front vehicle, and front vehicles in the adjacent lanes (these vehicles are collectively referred to as generalized preceding vehicles in this research). However, understanding of the impact exerted by the above information on car-following behavior and traffic flow is limited. In this paper, a car-following model considering the average velocity of generalized preceding vehicles (GPV) is proposed to explore the impact and then calibrated with the next generation simulation (NGSIM) data utilizing the genetic algorithm. The neutral stability condition of the model is derived via linear stability analysis. Numerical simulation on the starting, braking and disturbance propagation process is implemented to further study features of the established model and traffic flow stability. Research results suggest that the fitting accuracy of the GPV model is 40.497% higher than the full velocity difference (FVD) model. Good agreement between the theoretical analysis and the numerical simulation reveals that motion state information of GPV can stabilize traffic flow of following vehicles and thus alleviate traffic congestion.

scholarly journals A New Car-Following Model with Consideration of Dynamic Safety Distance

2018 ◽  
Vol 2018 ◽  
pp. 1-5
Author(s):  
Tao Wang ◽  
Jing Zhang ◽  
Guangyao Li ◽  
Keyu Xu ◽  
Shubin Li
Keyword(s):  
Traffic Flow ◽  
Velocity Model ◽  
Safe Distance ◽  
Optimal Velocity ◽  
New Model ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Safety Distance ◽  
Car Following Model ◽  
The Impact

In the traditional optimal velocity model, safe distance is usually a constant, which, however, is not representative of actual traffic conditions. This paper attempts to study the impact of dynamic safety distance on vehicular stream through a car-following model. Firstly, a new car-following model is proposed, in which the traditional safety distance is replaced by a dynamic term. Then, the phase diagram in the headway, speed, and sensitivity spaces is given to illustrate the impact of a variable safe distance on traffic flow. Finally, numerical methods are conducted to examine the performance of the proposed model with regard to two aspects: compared with the optimal velocity model, the new model can suppress traffic congestion effectively and, for different safety distances, the dynamic safety distance can improve the stability of vehicular stream. Simulation results suggest that the new model is able to enhance traffic flow stability.

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